作　　者： ; ;

机构地区： 华南理工大学计算机科学与工程学院

出　　处： 《计算机应用》 2009年第7期1921-1923,共3页

摘　　要： 为了有效地简化稠密采样点模型,提出了一种基于面元(surfel)重建的点模型简化方法。该算法首先对每个采样点面元的初始半径进行估算,并同时根据曲率的变化确定每个面元的简化权值;然后采用surfel合并的方法来聚合、减少surfel图元的数量,按照计算的surfel权值,确定surfel合并的顺序,合并并重建成一个新的surfel,合并过程中判断误差是否满足要求,满足则合并成功。如此迭代,直到surfel合并引起的误差达到阈值或surfel权值达到某个给定值。实验结果表明该算法能有效减少稠密采样点模型的点数,且在相同误差控制下简化率高于一般的基于纯采样点的简化算法;同时,简化模型能很好地保持原始模型的几何形状,防止简化后表面空洞现象的产生。 To efficiently simplify the densely sampled point model, a point sample data reduction method based on surfel reconstruction was presented. The surfel radius was generated and surfel decimation coefficient based on curve was made. According to surfel decimation coefficient, surfels were combined and a new surfel was generated based on given error. The point model was returned when the error reached given value or the surfel coefficient reached given value. Experimental results show that the algorithm can effectively simplify the dense sampled point models, and the decimation ratio is higher than other point decimation algorithm under control of the same error; the simplified model can preserve the original geometric shapes very well and prevent surface inanition.

关 键 词： 点模型 面元 简化

领　　域： [自动化与计算机技术] [自动化与计算机技术]